matrixdist (Q52496): Difference between revisions

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@@ Property / last update @@
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+Tools for phase-type distributions including the following variants:    continuous, discrete, multivariate, in-homogeneous, right-censored, and regression.     Methods for functional evaluation, simulation and estimation using the     expectation-maximization (EM) algorithm are provided for all models.    The methods of this package are based on the following references.    Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM algorithm,    Olsson, M. (1996). Estimation of phase-type distributions from censored data,    Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60>,    Albrecher, H., Bladt, M., & Yslas, J. (2022) <doi:10.1111/sjos.12505>,    Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2022) <doi:10.1016/j.insmatheco.2022.08.001>,    Bladt, M., & Yslas, J. (2022) <doi:10.1080/03461238.2022.2097019>,    Bladt, M. (2022) <doi:10.1017/asb.2021.40>,    Bladt, M. (2023) <doi:10.1080/10920277.2023.2167833>,    Albrecher, H., Bladt, M., & Mueller, A. (2023) <doi:10.1515/demo-2022-0153>,    Bladt, M. & Yslas, J. (2023) <doi:10.1016/j.insmatheco.2023.02.008>.
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+Martin Bladt
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+Jorge Yslas
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+GNU General Public License, version 3.0
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@@ Property / imports: Rcpp / rank @@
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@@ Property / imports: nnet / rank @@
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@@ Property / imports @@
+reshape2
@@ Property / imports: reshape2 / rank @@
+Normal rank
@@ Property / cites work @@
+Inhomogeneous phase-type distributions and heavy tails
+Normal rank
@@ Property / cites work @@
+Fitting inhomogeneous phase‐type distributions to data: the univariate and the multivariate case
+Normal rank
@@ Property / cites work @@
+Mortality modeling and regression with matrix distributions
+Normal rank
@@ Property / cites work @@
+Phase-type mixture-of-experts regression for loss severities
+Normal rank
@@ Property / cites work @@
+PHASE-TYPE DISTRIBUTIONS FOR CLAIM SEVERITY REGRESSION MODELING
+Normal rank
@@ Property / cites work @@
+A Tractable Class of Multivariate Phase-Type Distributions for Loss Modeling
+Normal rank
@@ Property / cites work @@
+Joint lifetime modeling with matrix distributions
@@ Property / cites work: Joint lifetime modeling with matrix distributions / rank @@
+Normal rank
@@ Property / cites work @@
+Robust claim frequency modeling through phase-type mixture-of-experts regression
+Normal rank
@@ Property / source code repository @@
+https://github.com/cran/BayesNet
@@ Property / source code repository: https://github.com/cran/BayesNet / rank @@
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@@ Property / depends on software @@
+R
@@ Property / depends on software: R / rank @@
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@@ Property / depends on software: R / qualifier @@
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@@ links / mardi / name / links / mardi / name @@
+Software:52496

Latest revision as of 12:28, 14 April 2025

Statistics for Matrix Distributions

Language	Label	Description	Also known as
English	matrixdist	Statistics for Matrix Distributions

Statements

instance of

R package

0 references

software version identifier

1.1.7

publication date

31 March 2023

0 references

1.1.8

publication date

7 April 2023

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1.0.1

publication date

15 February 2021

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1.0.2

publication date

26 February 2021

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1.0

publication date

8 January 2021

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1.1.0

publication date

17 June 2021

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1.1.2

publication date

18 June 2021

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1.1.3

publication date

3 September 2021

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1.1.4

publication date

13 September 2022

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1.1.5

publication date

29 September 2022

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1.1.6

publication date

16 October 2022

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1.1.9

publication date

8 August 2023

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8 August 2023

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description

Tools for phase-type distributions including the following variants: continuous, discrete, multivariate, in-homogeneous, right-censored, and regression. Methods for functional evaluation, simulation and estimation using the expectation-maximization (EM) algorithm are provided for all models. The methods of this package are based on the following references. Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM algorithm, Olsson, M. (1996). Estimation of phase-type distributions from censored data, Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60>, Albrecher, H., Bladt, M., & Yslas, J. (2022) <doi:10.1111/sjos.12505>, Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2022) <doi:10.1016/j.insmatheco.2022.08.001>, Bladt, M., & Yslas, J. (2022) <doi:10.1080/03461238.2022.2097019>, Bladt, M. (2022) <doi:10.1017/asb.2021.40>, Bladt, M. (2023) <doi:10.1080/10920277.2023.2167833>, Albrecher, H., Bladt, M., & Mueller, A. (2023) <doi:10.1515/demo-2022-0153>, Bladt, M. & Yslas, J. (2023) <doi:10.1016/j.insmatheco.2023.02.008>.

0 references

0 references

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GNU General Public License, version 3.0

0 references

imports

Rcpp

0 references